Exposure to nanomaterials in consumer spray products available in the UK

Products containing nanomaterials (NMs) (size < 100 nanometres) are rapidly entering the market, however little is known about inhalation exposures to NMs from their use. Here, we analysed representative consumer spray products available in the UK that claim (or are expected) to contain NMs, to assess potential NM exposure levels during use. In the absence of a UK-focused product inventory, we searched “The Nanodatabase” (nanodb.dk), which listed 269 (out of 3001) products for which inhalation was identified as an exposure pathway. None were available over-the-counter at large stores, but 40 were available on “.co.uk” websites (mainly Amazon). We obtained a representative sample (based on product type and claimed content e.g. silver, silica, gold) and found that 12 out of 16 products contained detectable NMs. We used a multi-method approach to characterise the NMs; inductively-coupled plasma mass spectrometry (ICP-MS), ultraviolet-visible spectroscopy and energy-dispersive x-ray spectroscopy to assess NM composition, and dynamic light scattering, nanoparticle tracking analysis, transmission electron microscopy and single particle ICP-MS to determine particle size and shape. The sizes of the airborne particles/droplets produced by spraying a sub-set (6) of these products were measured using aerodynamic and mobility particle sizers, demonstrating the presence of inhalable aerosols. Whilst 5 out of 6 products clearly contained NMs, only 3 produced aerosols in the nano-size range, suggesting that other constituents (e.g. solvent, fragrance) make up the bulk of the aerosol mass. Using the data generated, quantities of NMs inhaled when using these products can be estimated, which is important for appropriate risk characterisation

A versatile platform for gas-phase molecular polaritonics

Strong cavity coupling of gas-phase molecules will enable studies of benchmark chemical processes under strong light-matter interactions with a high level of experimental control and no solvent effects. We recently demonstrated the formation of gas-phase molecular polaritons by strongly coupling a bright rovibrational transition of methane to a Fabry-P\'erot optical cavity mode inside a cryogenic buffer gas cell. Here, we further explore the flexible capabilities of this infrastructure. We show that we can greatly increase the collective coupling strength of the molecular ensemble to the cavity by increasing the intracavity methane number density. In doing so, we access a multimode coupling regime in which many nested polaritonic states arise as the Rabi splitting approaches the cavity mode spacing. We explore polariton formation for cavity geometries of varying length, finesse, and mirror radius of curvature. We also report a proof-of-principle demonstration of rovibrational gas-phase polariton formation at room temperature. This experimental flexibility affords a great degree of control over the properties of molecular polaritons and opens up a wider range of simple molecular processes to future interrogation under strong cavity-coupling. We anticipate that ongoing work in gas-phase polaritonics will facilitate convergence between experimental results and theoretical models of cavity-altered chemistry and physics

Rovibrational Polaritons in Gas-Phase Methane

Polaritonic states arise when a bright optical transition of a molecular ensemble is resonantly matched to an optical cavity mode frequency. Here, we lay the groundwork to study the behavior of polaritons in clean, isolated systems by establishing a new platform for vibrational strong coupling in gas-phase molecules. We access the strong coupling regime in an intracavity cryogenic buffer gas cell optimized for the preparation of simultaneously cold and dense ensembles, and report a proof-of-principle demonstration in gas-phase methane. We strongly cavity-couple individual rovibrational transitions and probe a range of coupling strengths and detunings. We reproduce our findings with classical cavity transmission simulations in the presence of strong intracavity absorbers. This infrastructure provides a new testbed for benchmark studies of cavity-altered chemistry

Spatial Patterns and Sequential Sampling Plans for Estimating Densities of Stink Bugs (Hemiptera: Pentatomidae) in Soybean in the North Central Region of the United States

Stink bugs are an emerging threat to soybean (Fabales: Fabaceae) in the North Central Region of the United States. Consequently, region-specific scouting recommendations for stink bugs are needed. The aim of this study was to characterize the spatial pattern and to develop sampling plans to estimate stink bug population density in soybean fields. In 2016 and 2017, 125 fields distributed across nine states were sampled using sweep nets. Regression analyses were used to determine the effects of stink bug species [Chinavia hilaris (Say) (Hemiptera: Pentatomidae) and Euschistus spp. (Hemiptera: Pentatomidae)], life stages (nymphs and adults), and field locations (edge and interior) on spatial pattern as represented by variance–mean relationships. Results showed that stink bugs were aggregated. Sequential sampling plans were developed for each combination of species, life stage, and location and for all the data combined. Results for required sample size showed that an average of 40–42 sample units (sets of 25 sweeps) would be necessary to achieve a precision of 0.25 for stink bug densities commonly encountered across the region. However, based on the observed geographic gradient of stink bug densities, more practical sample sizes (5–10 sample units) may be sufficient in states in the southeastern part of the region, whereas impractical sample sizes (\u3e100 sample units) may be required in the northwestern part of the region. Our findings provide research-based sampling recommendations for estimating densities of these emerging pests in soybean

From Isotopes to TK Interviews: Towards Interdisciplinary Research in Fort Resolution and the Slave River Delta, Northwest Territories

Evolving research in Fort Resolution and the Slave River Delta, Northwest Territories, aims to improve understanding of how the natural ecosystem functions and responds to various environmental stressors, as well as to enhance the stewardship of natural resources and the capacity of local residents to respond to change. We seek to integrate approaches that span the natural and social sciences and traditional knowledge understandings of change, employing a research design developed in response to the concerns of a northern community. In doing so, we have strived for a research process that is collaborative, interdisciplinary, policy-oriented, and reflective of northern priorities. These elements characterize the new northern research paradigm increasingly promoted by various federal funding agencies, northern partners, and communities. They represent a holistic perspective in the pursuit of solutions to address complex environmental and socioeconomic concerns about impacts of climate change and resource development on northern societies. However, efforts to fulfill the objectives of this research paradigm are associated with a host of on-the-ground challenges. These challenges include (but are not restricted to) developing effective community partnerships and collaboration and documenting change through interdisciplinary approaches. Here we provide an overview of the components that comprise our interdisciplinary research program and offer an accounting of our formative experiences in confronting these challenges

Losing weights: Failure to recognize and act on weight loss documented in an electronic health record

Background: Involuntary weight loss is associated with higher mortality.  When this weight loss is unrecognized, opportunities for timely diagnosis of significant conditions may be missed.  Objective:To use electronic health record (EHR) data to estimate the frequency of unrecognized involuntary weight loss and its implications. Methods: We performed a retrospective analysis of the weights recorded in an EHR of 100,000 adult patients seen in outpatient clinics over a five-year period using a novel data visualization and review tool.  We reviewed charts of a random sample of 170 patients experiencing weight loss periods.   Our outcomes included determinations of whether weight loss 1) was voluntary vs. involuntary; 2) was recognized and documented; and 3) possible explanations identifiable at the index visit or within the subsequent two years.  Results: Of 170 randomly-selected weight loss periods reviewed, 22 (13%) were involuntary, 36 (21%) were voluntary and 112 (66%) were indeterminate.  Sixty-six (39%) weight loss periods were recognized by clinician at the index visits and an additional 3 (1%) at the next PCP visits.  Possible explanations for weight loss emerged in the subsequent two years including medical conditions in 60 (45%), psycho-social conditions in 19 (14%), erroneous data entry in 9 (7%), voluntary weight loss in 8 (6%),  and postpartum weight loss in 6 (4%).   No possible explanations were found in 32 (24%).   Conclusions:Periods of weight loss were common, often involuntary and frequently not recognized or documented.  Many patients with involuntary weight loss had potential explanations that emerged within the subsequent two years

Using a Service Oriented Architecture Approach to Clinical Decision Support: Performance Results from Two CDS Consortium Demonstrations

The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions

Accurate Machine Learning Atmospheric Retrieval via a Neural Network Surrogate Model for Radiative Transfer

Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each model parameter, given observed spectra. This inference is computationally expensive, as it requires many executions of a costly radiative transfer (RT) simulation for each set of sampled model parameters. Machine learning (ML) has recently been shown to provide a significant reduction in runtime for retrievals, mainly by training inverse ML models that predict parameter distributions, given observed spectra, albeit with reduced posterior accuracy. Here we present a novel approach to retrieval by training a forward ML surrogate model that predicts spectra given model parameters, providing a fast approximate RT simulation that can be used in a conventional Bayesian retrieval framework without significant loss of accuracy. We demonstrate our method on the emission spectrum of HD 189733 b and find good agreement with a traditional retrieval from the Bayesian Atmospheric Radiative Transfer (BART) code (Bhattacharyya coefficients of 0.9843--0.9972, with a mean of 0.9925, between 1D marginalized posteriors). This accuracy comes while still offering significant speed enhancements over traditional RT, albeit not as much as ML methods with lower posterior accuracy. Our method is ~9x faster per parallel chain than BART when run on an AMD EPYC 7402P central processing unit (CPU). Neural-network computation using an NVIDIA Titan Xp graphics processing unit is 90--180x faster per chain than BART on that CPU.Comment: 16 pages, 4 figures, submitted to PSJ 3/4/2020, revised 1/22/2021. Text restructured and updated for clarity, model updated and expanded to work for range of hot Jupiters, results/plots updated, two new appendices to further justify model selection and methodolog

Collaborating in Tough Times: Responding to State Cuts

This presentation was for a panel session with librarians from school, public, academic, and the North Texas Library Partners (NTLP) at the Texas Library Association (TLA) annual conference. In this presentation, the authors discuss collaboration strategies during difficult financial periods and funding cuts

The EGNoG Survey: Molecular Gas in Intermediate-Redshift Star-Forming Galaxies

We present the Evolution of molecular Gas in Normal Galaxies (EGNoG) survey, an observational study of molecular gas in 31 star-forming galaxies from z=0.05 to z=0.5, with stellar masses of (4-30)x10^10 M_Sun and star formation rates of 4-100 M_Sun yr^-1. This survey probes a relatively un-observed redshift range in which the molecular gas content of galaxies is expected to have evolved significantly. To trace the molecular gas in the EGNoG galaxies, we observe the CO(1-0) and CO(3-2) rotational lines using the Combined Array for Research in Millimeter-wave Astronomy (CARMA). We detect 24 of 31 galaxies and present resolved maps of 10 galaxies in the lower redshift portion of the survey. We use a bimodal prescription for the CO to molecular gas conversion factor, based on specific star formation rate, and compare the EGNoG galaxies to a large sample of galaxies assembled from the literature. We find an average molecular gas depletion time of 0.76 \pm 0.54 Gyr for normal galaxies and 0.06 \pm 0.04 Gyr for starburst galaxies. We calculate an average molecular gas fraction of 7-20% at the intermediate redshifts probed by the EGNoG survey. By expressing the molecular gas fraction in terms of the specific star formation rate and molecular gas depletion time (using typical values), we also calculate the expected evolution of the molecular gas fraction with redshift. The predicted behavior agrees well with the significant evolution observed from z~2.5 to today.Comment: Accepted for publication in the Astrophysical Journal; 29 pages, 20 figures, 6 table